Human Nature

Whether you are evaluating
your entire supply chain or a specific node within it, is important never
to forget you are dealing with humans. All around us today is talk of
metrics, dashboards and SCORcards, all of which provide important
information on supply chain performance. But information is only valuable
if you understand it and apply it in balance with the human element. By
this, I mean that it is human nature to want to know “what is
expected of me, and how did I do against that expectation.” For this
reason, metrics and performance data can be vital to evaluating supply
chain success. Let’s take a specific distribution center as an
example as to how we can set a performance expectation and measure against
it.

Within a distribution center (DC), control is essential to any goal-setting system. One method of
establishing control within a DC is to determine the instantaneous rates at
which you expect work to occur and when someone is executing it. For each
job function, the leadership must calculate the instantaneous rate at work
performance based on the specific market conditions that exist in a given
DC. You can calculate the expected rate for each job function by utilizing
a combination of order profile, travel distance and material handling
capability. When doing this, it is important to remember that in a variable
workload environment (which most beverage DCs are) the expected rate for
each activity is also variable. Therefore, management must calculate the
instantaneous rate on a daily basis.

Again, order profiles, travel distances and material
handling capability drive the rate of work performance for each function.
Order profile refers to the complexity associated with customer orders. In
a DC operation, the following drive the rate of work performance:

the number of full pallets vs. mixed
pallets.

the number of layers vs. loose cases on a mixed
pallet

the number of SKUs on a mixed pallet

the number of cases per SKU for loose cases.

Distance refers to the aggregate travel distance (on a
material handling vehicle or on foot) required
to fulfill an assigned task. As a rule of thumb, travel distance results in
70 percent of the time associated with picking a full pallet and only 30
percent of the time associated with picking an individual case. Material
handling factors refer to the type of material handling equipment used for
loading in the various loading functions. For example, single vs.
double-wide forklift attachments, double-length pallet jacks and layer pick
devices all impact the rate of work performance.

Just so you make the connection to the supply chain
— on a larger scale, profile (make-up of a trailer), travel distance
and truck capability drive down transportation costs.

With an approach in place to set targets and answer
the “What does the company expect of me?” question, the second
element of human nature: “How did I do against the
expectation?” comes into play. Unfortunately, many organizations only
put the latter into place and measure performance without any type of
reference point.

An accurate performance measurement system (capable of
tracking individual performance) is an essential step in any supply chain
improvement effort. At the warehouse, level many companies utilize a
computerized warehouse management system (WMS) to develop performance
measures. If you do not have a WMS, you can still effectively measure
performance using the Microsoft suite of tools. Even companies that have a
WMS will sometimes create performance measure “off-line”
depending on the measure being pursued.

Whatever tool you decide to use, measuring
productivity at which performers can actually execute work provides
management with insight into the overall capability and capacity of the
supply chain. To truly determine the capability of a given DC, you must
know the actual instantaneous rate and utilization of each individual and
actual instantaneous rate and utilization by function. Individual refers to
each performer within the operation. Function refers to the various
discrete job functions within an operation. Therefore, resolution into each
performer in each job function will determine overall capability of a DC.

In addition to instantaneous rate, I also mentioned
utilization. Where instantaneous rate defines the speed at which work is
performed while a worker is actively engaged in a job function, utilization
represents the amount of time a worker spent working as a percentage of the
total time available to work. In a conventional DC, a reasonable target for
utilization is 85 percent. This means a worker should be actively engaged
in a job for 6.75 hours out of an eight-hour shift. The 1 hour and 15
minutes of lost time allows for breaks, pre-shift meetings and post-shift
clean-up activities.

When you multiply the instantaneous rate by
utilization, you achieve productivity.

The inability of workers to achieve the productivity
targets set by management inevitably drives cost into the supply chain. For
example, if staffing levels are set on the basis of an order picker
achieving productivity of 240 cases per hour, and an order picker only
achieves a level of 180, the cost of labor increases by 25 percent. This 25
percent increase excludes the additional overtime hours needed to fulfill
the required daily volume.

If you have the productivity expectation and the
productivity results, you now have the information you need to make
accurate managerial decisions at the same time you satisfy human nature.
With this information, you can also identify the root cause of poor
performance.

Although we focused on the DC level for this
discussion, you can apply the same process at all levels of the supply
chain. The trick is to set accurate expectations, calculate accurate
measurements, use the information to identify action plans when performance
falls behind expectation… and never forget human nature. BI

Ned Bauhof’s “beverage team” has
executed more than 100 projects in 85 locations in 10 countries. Ned is a
principal with York, Pa.-based St. Onge Co., a material handling and
logistics consulting firm specializing in the planning, engineering and
implementation of advanced material handling, information and control
systems supporting logistics, manufacturing and distribution since 1983 (www.stonge.com). Ned can be reached at 717/840-8181 or by email at
NedBauhof@stonge.com.

Finding the cause

If a distribution center’s productivity is lower
than expected, there may be a number of reasons, including:

Workers are not following the standard work
practices.

No one properly prepared the DC before the
shift.

The performer may be physically unable to
perform work.

The worker may be purposely working at slow
rate. It happens.

Or there may be utilization-related reasons,
including:

Insufficient work to keep workers busy
throughout the shift.

Worker may have been doing other tasks
unrelated to their function during the shift

Time may be lost waiting for a work
assignment.

Inability to account for a worker’s
time. It happens.

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